Low-frequency nonsynonymous variants inFKBPLandARPC1Bgenes are associated with breast cancer risk in Chinese women

Pan-cancer identified ARPC1B as a promising target for tumor immunotherapy and prognostic biomarker, particularly in READ

ARPC1B encodes the protein known as actin-related protein 2/3 complex subunit 1 B (ARPC1B), which controls actin polymerization in the human body. Although ARPC1B has been linked to several human malignancies, its function in these cancers remains unclear. TCGA, GTEx, CCLE, Xena, CellMiner, TISIDB, and molecular signature databases were used to analyze ARPC1B expression in cancers. Visualization of data was primarily achieved using R language, version 4.0. Nineteen tumors exhibited high levels of ARPC1B expression, which were associated with different tumor stages and significantly affected the prognosis of various cancers. The level of ARPC1B expression substantially connected the narrative of ARPC1B expression with several TMB cancers and showed significant changes in MSI. Additionally, tolerance to numerous anticancer medications has been linked to high ARPC1B gene expression. Using Gene Set Variation Analysis/Gene Set Enrichment Analysisanalysis and concentrating on Rectum adenocarcinoma (READ), we thoroughly examined the molecular processes of the ARPC1B gene in pan-cancer. Using WGCNA, we examined the co-expression network of READ and ARPC1B. Meanwhile, ten specimens were selected for immunohistochemical examination, which showed high expression of ARPC1B in READ. Human pan-cancer samples show higher ARPC1B expression than healthy tissues. In many malignancies, particularly READ, ARPC1B overexpression is associated with immune cell infiltration and a poor prognosis. These results imply that the molecular biomarker ARPC1B may be used to assess the prognosis and immune infiltration of patients with READ.

Inositol 1,4,5-trisphosphate receptor gene variants are related to the risk of breast cancer in a Chinese population

BACKGROUND

Mammalian inositol 1,4,5-trisphosphate receptor (ITPR) genes encode ubiquitously expressed endoplasmic reticulum Ca²⁺ channels that have recently been shown to be closely linked to the pathogenesis of several cancers. However, few studies to date have explored associations between ITPR gene family single nucleotide polymorphisms (SNPs) and breast cancer risk.

METHODS

In the present case-control study, 12 SNPs in the potential functional regions of the ITPR1, ITPR2, and ITPR3 genes were genotyped using an Illumina Infinium® Beadchip in 2095 Chinese women (1032 cases and 1063 controls).

RESULTS

Multivariate logistic regression analyses indicated that a missense SNP in the ITPR3 coding region (rs2229642) was significantly related to breast cancer risk when using an additive model in this study (rs2229642-adjusted odds ratio = 1.40, 95% confidence interval = 1.12-1.74, p = 2.97 × 10^-3 ). Expression quantitative trait loci analyses indicated that the SNP rs2229642 was associated with reduced ITPR3 expression levels (p = 3.2 × 10^-7 ) and with marked reductions in the expressions of several proximal genes, including BAK1, GRM4, HLA-DOB, and UQCC2 (p = 0.013, 0.018, 3.4 × 10^-3 , 3.8 × 10^-5 ), suggesting that it may further regulate other genes associated with oncogenic susceptibility. Kaplan-Meier analyses indicated that the patients with higher ITPR3 expression exhibited significantly poorer outcomes compared to the patients with lower expression of this gene (hazard ratio = 1.11, 95% confidence interval = 1-1.23, p = 0.046).

CONCLUSIONS

The results indicated that genetic variant in the coding region of ITPR3 gene may regulate the expressions of its host and some other cancer-related genes, as well as act as potential predictive biomarker for susceptibility to breast cancer in the Chinese population.

Functions of the Hsp90-Binding FKBP Immunophilins

The Hsp90 chaperone is known to interact with a diverse array of client proteins. However, in every case examined, Hsp90 is also accompanied by a single or several co-chaperone proteins. One class of co-chaperone contains a tetratricopeptide repeat (TPR) domain that targets the co-chaperone to the C-terminal region of Hsp90. Within this class are Hsp90-binding peptidylprolyl isomerases, most of which belong to the FK506-binding protein (FKBP) family. Despite the common association of FKBP co-chaperones with Hsp90, it is abundantly clear that the client protein influences, and is often influenced by, the particular FKBP bound to Hsp90. Examples include Xap2 in aryl hydrocarbon receptor complexes and FKBP52 in steroid receptor complexes. In this chapter, we discuss the known functional roles played by FKBP co-chaperones and, where possible, relate distinctive functions to structural differences between FKBP members.

Coding variants in the PCNT and CEP295 genes contribute to breast cancer risk in Chinese women

BACKGROUND

Centrioles play pivotal roles in the assembly of centrosomes, their dysfunction is associated with multiple inherited diseases or cancers. To date, few studies have focused on the associations between coding single nucleotide polymorphisms (SNPs) in the centriole duplication cycle genes and the risk of breast cancer in Chinese women.

METHODS

Twenty-one SNPs were selected from the coding regions of 10 critical centriole genes. The associations between the selected SNPs and breast cancer susceptibility were assessed in a case-control study of Chinese women, which included 1032 cases and 1063 controls. Potential biological functions in the influence of protein stability and the profile of expression quantitative trait loci (eQTL) of the identified SNPs were further evaluated using in silico databases.

RESULTS

Multivariate logistic regression analyses revealed that a missense SNP rs7279204 in PCNT was significantly associated with an increased risk of breast cancer (additive model: adjusted OR=1.19, 95% CI: 1.02-1.38), while a missense SNP rs77922978 in CEP295 was significantly associated with a decreased risk of breast cancer (additive model: adjusted OR=0.74, 95% CI: 0.56-0.97). Stratification analyses suggested that rs7279204 and rs77922978 exhibited different effects among later first live birth, ER-negative and PR-negative women (P<0.05). Moreover, rs77922978 showed significant differences for ER and PR status strata (heterogeneity test P=0.028, P=0.046). In addition, bioinformatic analyses indicated that the two variants may possess potential functions of reducing the protein stability of their host genes. Further eQTL analysis showed that the rs7279204 was not only correlated with the expression of its host gene PCNT, but also correlated with the expression of its nearby genes, implying its potential roles in regulation of some cancer susceptibility genes.

CONCLUSIONS

The SNPs rs7279204 and rs77922978 within the coding region of the PCNT and CEP295 genes may contribute to the susceptibility of breast cancer in Han Chinese population.

Potential functional variants of KIAA genes are associated with breast cancer risk in a case control study

Background

KIAA genes identified in the Kazusa cDNA-sequencing project may play important roles in biological processes and are involved in carcinogenesis of many cancers. Genetic variants of KIAA genes are implicated in the abnormal expression of these genes and are linked to susceptibility of several human complex diseases.

Methods

The differentially expressed KIAA genes were screened and identified in The Cancer Genome Atlas (TCGA) database of breast cancer. A total of 48 variants located in the 28 KIAA genes were selected to investigate the associations between polymorphism and breast cancer in 1,032 cases and 1,063 cancer-free controls in a Chinese population.

Results

Two coding variants, which included a SNP rs2306369 in KIAA1109 and a SNP rs1205434 in KIAA1755, were identified to be associated with the incidences of breast cancer. Logistic regression analysis showed that the SNP rs2306369 G allele was associated with a decreased risk of breast cancer (additive model: OR =0.81, 95% CI: 0.66-0.99, P=0.038), whereas the SNP rs1205434 A allele was involved with a higher risk of breast cancer (additive model: OR =1.19, 95% CI: 1.02-1.38, P= 0.025). Further stratified analysis revealed that the SNP rs1205434 showed a significant difference for age at menarche strata (heterogeneity test P=0.009). Multiplicative interaction analysis indicated that there was positive multiplicative interaction between the SNP rs1205434 and menarche age (OR =1.09, 95% CI: 1.01-1.17, P=0.036). Additionally, expression quantitative trait loci analysis revealed that the SNP rs1205434 A allele could decrease the KIAA1755 expression in the Genotype-Tissue Expression (GTEx) database (P=0.002). The Kaplan-Meier plotter showed that breast cancer patients with high KIAA1755 expression have significantly better outcomes than those with low levels of expression (HR =0.84, 95% CI: 0.72-0.99, P=0.033).

Conclusions

The results indicate that the genetic variants (rs2306369 and rs1205434) in the coding region of KIAA1109 and KIAA1755 respectively may affect Chinese females' breast cancer susceptibility and act as potential predictive biomarkers for breast cancer.

Convergent network effects along the axis of gene expression during prostate cancer progression

Background

Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues.

Results

Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a sub-network consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers.

Conclusions

This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions.

Quantifying posterior effect size distribution of susceptibility loci by common summary statistics

Testing millions of single nucleotide polymorphisms (SNPs) in genetic association studies has become a standard routine for disease gene discovery. In light of recent re-evaluation of statistical practice, it has been suggested that p-values are unfit as summaries of statistical evidence. Despite this criticism, p-values contain information that can be utilized to address the concerns about their flaws. We present a new method for utilizing evidence summarized by p-values for estimating odds ratio (OR) based on its approximate posterior distribution. In our method, only p-values, sample size, and standard deviation for ln(OR) are needed as summaries of data, accompanied by a suitable prior distribution for ln(OR) that can assume any shape. The parameter of interest, ln(OR), is the only parameter with a specified prior distribution, hence our model is a mix of classical and Bayesian approaches. We show that our method retains the main advantages of the Bayesian approach: it yields direct probability statements about hypotheses for OR and is resistant to biases caused by selection of top-scoring SNPs. Our method enjoys greater flexibility than similarly inspired methods in the assumed distribution for the summary statistic and in the form of the prior for the parameter of interest. We illustrate our method by presenting interval estimates of effect size for reported genetic associations with lung cancer. Although we focus on OR, the method is not limited to this particular measure of effect size and can be used broadly for assessing reliability of findings in studies testing multiple predictors.

Exploring the role of low-frequency and rare exonic variants in alcohol and tobacco use

BACKGROUND

Alcohol and tobacco use are heritable phenotypes. However, only a small number of common genetic variants have been identified, and common variants account for a modest proportion of the heritability. Therefore, this study aims to investigate the role of low-frequency and rare variants in alcohol and tobacco use.

METHODS

We meta-analyzed ExomeChip association results from eight discovery cohorts and included 12,466 subjects and 7432 smokers in the analysis of alcohol consumption and tobacco use, respectively. The ExomeChip interrogates low-frequency and rare exonic variants, and in addition a small pool of common variants. We investigated top variants in an independent sample in which ICD-9 diagnoses of "alcoholism" (N = 25,508) and "tobacco use disorder" (N = 27,068) had been assessed. In addition to the single variant analysis, we performed gene-based, polygenic risk score (PRS), and pathway analyses.

RESULTS

The meta-analysis did not yield exome-wide significant results. When we jointly analyzed our top results with the independent sample, no low-frequency or rare variants reached significance for alcohol consumption or tobacco use. However, two common variants that were present on the ExomeChip, rs16969968 (p = 2.39 × 10^-7) and rs8034191 (p = 6.31 × 10^-7) located in CHRNA5 and AGPHD1 at 15q25.1, showed evidence for association with tobacco use.

DISCUSSION

Low-frequency and rare exonic variants with large effects do not play a major role in alcohol and tobacco use, nor does the aggregate effect of ExomeChip variants. However, our results confirmed the role of the CHRNA5-CHRNA3-CHRNB4 cluster of nicotinic acetylcholine receptor subunit genes in tobacco use.

Germline Variation and Breast Cancer Incidence: A Gene-Based Association Study and Whole-Genome Prediction of Early-Onset Breast Cancer

Background: Although germline genetics influences breast cancer incidence, published research only explains approximately half of the expected association. Moreover, the accuracy of prediction models remains low. For women who develop breast cancer early, the genetic architecture is less established.Methods: To identify loci associated with early-onset breast cancer, gene-based tests were carried out using exome array data from 3,479 women with breast cancer diagnosed before age 50 and 973 age-matched controls. Replication was undertaken in a population that developed breast cancer at all ages of onset.Results: Three gene regions were associated with breast cancer incidence: FGFR2 (P = 1.23 × 10^-5; replication P < 1.00 × 10^-6), NEK10 (P = 3.57 × 10^-4; replication P < 1.00 × 10^-6), and SIVA1 (P = 5.49 × 10^-4; replication P < 1.00 × 10^-6). Of the 151 gene regions reported in previous literature, 19 (12.5%) showed evidence of association (P < 0.05) with the risk of early-onset breast cancer in the early-onset population. To predict incidence, whole-genome prediction was implemented on a subset of 3,076 participants who were additionally genotyped on a genome wide array. The whole-genome prediction outperformed a polygenic risk score [AUC, 0.636; 95% confidence interval (CI), 0.614-0.659 compared with 0.601; 95% CI, 0.578-0.623], and when combined with known epidemiologic risk factors, the AUC rose to 0.662 (95% CI, 0.640-0.684).Conclusions: This research supports a role for variation within FGFR2 and NEK10 in breast cancer incidence, and suggests SIVA1 as a novel risk locus.Impact: This analysis supports a shared genetic etiology between women with early- and late-onset breast cancer, and suggests whole-genome data can improve risk assessment. Cancer Epidemiol Biomarkers Prev; 27(9); 1057-64. ©2018 AACR.

Effects of potentially functional polymorphisms in suppressor of cytokine signaling 3 (SOCS3) on the risk of head and neck squamous cancer

BACKGROUND

Suppressor of cytokine signaling 3 (SOCS3) has been identified as an inhibitor of JAK/STAT pathway that plays a significant role in carcinogenesis. SOCS3 and JAK2 polymorphisms may influence the gene expression or function, contributing to the disease susceptibility; however, such effect has not been evaluated in head and neck squamous cell carcinoma (HNSCC).

METHODS

A case-control study was performed to test the associations of SOCS3 and JAK2 polymorphisms with risk of HNSCC in 576 cases and 1552 cancer-free controls from China. Seven potentially functional polymorphisms predicted by bioinformatics tools were genotyped using Infinium BeadChip platform. The association between genotypes and HNSCC risk was estimated by computing odds ratios (ORs) and 95% confidence intervals (CIs) in univariate and multivariate logistic regression models.

RESULTS

We found that rs2280148 located at 3'-untranslated region of SOCS3 was significantly associated with an increased risk of HNSCC (additive model: adjusted OR = 1.21, 95% CI = 1.03-1.43, P = 0.021). Moreover, rs8064821 located in the promoter region of SOCS3 was linked with a decreased risk of the cancer (additive model: adjusted OR = 0.83, 95% CI = 0.71-0.97, P = 0.022). Combined analysis of these variants by the number of risk alleles showed a significant locus-dosage effect on the risk of HNSCC (P_trend = 0.006).

CONCLUSIONS

We provided the first evidence that SOCS3 polymorphisms may influence the risk of HNSCC, which could be applied as novel biomarkers to identify individuals at high risk of the disease.